Antenna Season Report Notebook¶

Josh Dillon, Last Revised January 2022

This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.

In [1]:
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
In [2]:
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
In [3]:
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')

antenna = "32"
csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_"
auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
In [4]:
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))

Antenna 32 Report

In [5]:
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
In [6]:
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')

Found 33 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_
Found 31 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
In [7]:
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0

def jd_to_summary_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'

def jd_to_auto_metrics_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'

Load relevant info from summary CSVs¶

In [8]:
this_antenna = None
jds = []

# parse information about antennas and nodes
for csv in csvs:
    df = pd.read_csv(csv)
    for n in range(len(df)):
        # Add this day to the antenna
        row = df.loc[n]
        if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
            antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
        else:
            antnum = int(row['Ant'])
        if antnum != int(antenna):
            continue
        
        if np.issubdtype(type(row['Node']), np.integer):
            row['Node'] = str(row['Node'])
        if type(row['Node']) == str and row['Node'].isnumeric():
            row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
            
        if this_antenna is None:
            this_antenna = Antenna(row['Ant'], row['Node'])
        jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
        jds.append(jd)
        this_antenna.add_day(jd, row)
        break
In [9]:
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]

df = pd.DataFrame(to_show)

# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
    df[col] = bar_cols[col]

z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
    df[col] = z_score_cols[col]

ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
    df[col] = ant_metrics_cols[col]

redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]   
for col in redcal_cols:
    df[col] = redcal_cols[col]

# style dataframe
table = df.style.hide_index()\
          .applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
          .background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
          .background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
          .applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
          .format({col: '{:,.4f}'.format for col in z_score_cols}) \
          .format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
          .format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
          .set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])

Table 1: Per-Night RTP Summary Info For This Atenna¶

This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.

In [10]:
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))

Antenna 32, Node N02:

Out[10]:
JDs A Priori Status Auto Metrics Flags Dead Fraction in Ant Metrics (Jee) Dead Fraction in Ant Metrics (Jnn) Crossed Fraction in Ant Metrics Flag Fraction Before Redcal Flagged By Redcal chi^2 Fraction ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score Average Dead Ant Metric (Jee) Average Dead Ant Metric (Jnn) Average Crossed Ant Metric Median chi^2 Per Antenna (Jee) Median chi^2 Per Antenna (Jnn)
2459848 RF_maintenance 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 27.986665 27.608595 2.800212 3.246449 4.014877 8.971015 2.434188 3.735577 0.6154 0.6611 0.2128 2.937848 2.610756
2459847 RF_maintenance 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 27.758870 28.871353 3.304444 3.017204 6.559398 16.311734 26.357800 32.949931 0.6183 0.6094 0.2895 3.649710 3.495081
2459846 RF_maintenance 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 23.906404 15.135903 1.671592 3.557778 12.661646 11.613998 12.610499 0.068879 0.7458 0.6598 0.3327 3.639624 3.789819
2459845 RF_maintenance 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 37.265146 20.620394 4.098079 7.067780 7.448025 24.556941 18.807368 53.361523 0.6468 0.7124 0.2603 3.353997 1.491647
2459844 RF_maintenance 100.00% 100.00% 100.00% 0.00% - - 10.360278 9.696247 3.195813 2.665840 0.942529 0.084265 -0.869858 0.049044 0.0249 0.0247 0.0003 nan nan
2459843 RF_maintenance 100.00% 0.66% 0.66% 0.00% 100.00% 0.00% 47.407932 4.508289 2.163426 5.195471 4.025041 8.072116 27.645746 123.954101 0.6506 0.7464 0.3498 4.132497 3.980561
2459839 RF_maintenance 100.00% - - - - - 12.275483 16.424300 111.401620 98.790208 nan nan -29.231224 -30.920487 nan nan nan nan nan
2459838 RF_maintenance 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 31.876068 32.205870 1.521535 1.063851 4.484820 6.653010 0.326768 -0.313669 0.0975 0.0957 0.0124 1.241524 1.243185
2459836 RF_maintenance - 100.00% 100.00% 0.00% - - nan nan nan nan nan nan nan nan 0.0326 0.0375 0.0008 nan nan
2459835 RF_maintenance 0.00% 100.00% 100.00% 0.00% - - -0.691824 -0.777760 -0.650646 -0.466687 -0.352360 -0.598096 -0.133660 0.557886 0.0323 0.0368 0.0010 nan nan
2459833 RF_maintenance 0.00% 100.00% 100.00% 0.00% - - 3.553846 2.416578 -0.293589 -0.592364 2.233617 -0.004896 -0.356334 0.814263 0.0287 0.0297 0.0006 nan nan
2459832 RF_maintenance 100.00% 0.00% 67.20% 0.00% 100.00% 0.00% 51.419364 44.286418 1.280876 0.784676 2.330268 1.320983 1.204436 -0.497536 0.6492 0.3950 0.3895 4.089397 3.269102
2459831 RF_maintenance 0.00% 100.00% 100.00% 0.00% - - 0.198557 1.044041 -0.161707 0.677463 1.004664 0.602369 -0.868663 1.164962 0.0327 0.0414 0.0006 nan nan
2459830 RF_maintenance 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 51.617781 42.442836 2.199469 1.407979 11.538321 15.805875 33.376908 45.771914 0.0985 0.0943 0.0131 1.301359 1.294334
2459829 RF_maintenance 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 59.902570 22.803635 2.244033 1.400890 11.698670 25.821387 74.503435 105.353687 0.0960 0.0860 0.0099 0.000000 0.000000
2459828 RF_maintenance 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 50.657228 0.052921 2.534774 2.545347 8.399044 5.958020 53.846806 41.172779 0.0935 0.0834 0.0138 0.939388 0.929780
2459827 RF_maintenance 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 44.409247 18.752342 3.107224 2.127258 9.959728 18.971340 42.695678 141.560125 0.0978 0.0859 0.0101 1.355255 1.355418
2459826 RF_maintenance 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 41.707145 33.159303 2.898309 2.068498 11.267753 15.114198 35.271350 42.951242 0.0746 0.0646 0.0032 1.345798 1.336421
2459825 RF_maintenance 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 36.657307 36.042927 1.582191 1.321208 11.366703 10.404887 30.721768 17.472658 0.0961 0.0906 0.0112 1.303284 1.297986
2459824 RF_maintenance 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 24.458371 17.931443 2.316899 1.788111 27.583863 28.314938 36.000489 66.819590 0.0935 0.0916 0.0113 1.182401 1.198020
2459823 RF_maintenance 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 5.614933 34.502261 4.472487 3.036750 2.965655 6.329502 2.684937 25.283167 0.0787 0.0915 0.0154 1.187893 1.198302
2459822 RF_maintenance 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 47.445175 9.417852 3.531708 1.718797 6.528212 14.033363 36.953200 149.813000 0.0927 0.0872 0.0128 1.205605 1.200640
2459821 RF_maintenance 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 54.116616 7.806622 3.584681 1.914256 8.193912 14.575296 20.277179 65.395526 0.0887 0.0793 0.0111 1.178706 1.182502
2459820 RF_maintenance 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 50.023709 11.825752 2.999050 2.331469 23.830093 42.318394 45.266283 50.351544 0.6598 0.6564 0.3489 6.446926 4.374442
2459817 RF_maintenance 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 44.159946 14.713926 2.782155 0.586606 9.527108 18.106058 16.218602 51.048984 0.7565 0.6221 0.3797 9.448519 4.417932
2459816 RF_maintenance 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 32.557568 29.850488 2.322337 1.856119 13.446395 15.464851 38.597595 51.830294 0.7603 0.5425 0.4044 5.543261 4.011910
2459815 RF_maintenance 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 36.414833 30.598530 2.588430 2.009225 10.960552 12.446353 33.521336 42.781157 0.7440 0.6076 0.3509 8.593179 7.380487
2459814 RF_maintenance 0.00% - - - - - nan nan nan nan nan nan nan nan nan nan nan nan nan
2459813 RF_maintenance 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% nan nan inf inf nan nan nan nan nan nan nan 0.000000 0.000000

Load antenna metric spectra and waterfalls from auto_metrics notebooks.¶

In [11]:
htmls_to_display = []
for am_html in auto_metric_htmls:
    html_to_display = ''
    # read html into a list of lines
    with open(am_html) as f:
        lines = f.readlines()
    
    # find section with this antenna's metric plots and add to html_to_display
    jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
    try:
        section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
    except ValueError:
        continue
    html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
    for line in lines[section_start_line + 1:]:
        html_to_display += line
        if '<hr' in line:
            htmls_to_display.append(html_to_display)
            break

Figure 1: Antenna autocorrelation metric spectra and waterfalls.¶

These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.

In [12]:
for i, html_to_display in enumerate(htmls_to_display):
    if i == 100:
        break
    display(HTML(html_to_display))

Antenna 32: 2459848

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
32 N02 RF_maintenance ee Shape 27.986665 27.608595 27.986665 3.246449 2.800212 8.971015 4.014877 3.735577 2.434188

Antenna 32: 2459847

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
32 N02 RF_maintenance nn Temporal Discontinuties 32.949931 28.871353 27.758870 3.017204 3.304444 16.311734 6.559398 32.949931 26.357800

Antenna 32: 2459846

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
32 N02 RF_maintenance ee Shape 23.906404 23.906404 15.135903 1.671592 3.557778 12.661646 11.613998 12.610499 0.068879

Antenna 32: 2459845

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
32 N02 RF_maintenance nn Temporal Discontinuties 53.361523 20.620394 37.265146 7.067780 4.098079 24.556941 7.448025 53.361523 18.807368

Antenna 32: 2459844

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
32 N02 RF_maintenance ee Shape 10.360278 10.360278 9.696247 3.195813 2.665840 0.942529 0.084265 -0.869858 0.049044

Antenna 32: 2459843

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
32 N02 RF_maintenance nn Temporal Discontinuties 123.954101 4.508289 47.407932 5.195471 2.163426 8.072116 4.025041 123.954101 27.645746

Antenna 32: 2459839

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
32 N02 RF_maintenance ee Power 111.401620 16.424300 12.275483 98.790208 111.401620 nan nan -30.920487 -29.231224

Antenna 32: 2459838

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
32 N02 RF_maintenance nn Shape 32.205870 32.205870 31.876068 1.063851 1.521535 6.653010 4.484820 -0.313669 0.326768

Antenna 32: 2459835

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
32 N02 RF_maintenance nn Temporal Discontinuties 0.557886 -0.777760 -0.691824 -0.466687 -0.650646 -0.598096 -0.352360 0.557886 -0.133660

Antenna 32: 2459833

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
32 N02 RF_maintenance ee Shape 3.553846 2.416578 3.553846 -0.592364 -0.293589 -0.004896 2.233617 0.814263 -0.356334

Antenna 32: 2459832

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
32 N02 RF_maintenance ee Shape 51.419364 51.419364 44.286418 1.280876 0.784676 2.330268 1.320983 1.204436 -0.497536

Antenna 32: 2459831

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
32 N02 RF_maintenance nn Temporal Discontinuties 1.164962 0.198557 1.044041 -0.161707 0.677463 1.004664 0.602369 -0.868663 1.164962

Antenna 32: 2459830

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
32 N02 RF_maintenance ee Shape 51.617781 51.617781 42.442836 2.199469 1.407979 11.538321 15.805875 33.376908 45.771914

Antenna 32: 2459829

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
32 N02 RF_maintenance nn Temporal Discontinuties 105.353687 22.803635 59.902570 1.400890 2.244033 25.821387 11.698670 105.353687 74.503435

Antenna 32: 2459828

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
32 N02 RF_maintenance ee Temporal Discontinuties 53.846806 0.052921 50.657228 2.545347 2.534774 5.958020 8.399044 41.172779 53.846806

Antenna 32: 2459827

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
32 N02 RF_maintenance nn Temporal Discontinuties 141.560125 44.409247 18.752342 3.107224 2.127258 9.959728 18.971340 42.695678 141.560125

Antenna 32: 2459826

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
32 N02 RF_maintenance nn Temporal Discontinuties 42.951242 33.159303 41.707145 2.068498 2.898309 15.114198 11.267753 42.951242 35.271350

Antenna 32: 2459825

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
32 N02 RF_maintenance ee Shape 36.657307 36.042927 36.657307 1.321208 1.582191 10.404887 11.366703 17.472658 30.721768

Antenna 32: 2459824

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
32 N02 RF_maintenance nn Temporal Discontinuties 66.819590 24.458371 17.931443 2.316899 1.788111 27.583863 28.314938 36.000489 66.819590

Antenna 32: 2459823

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
32 N02 RF_maintenance nn Shape 34.502261 34.502261 5.614933 3.036750 4.472487 6.329502 2.965655 25.283167 2.684937

Antenna 32: 2459822

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
32 N02 RF_maintenance nn Temporal Discontinuties 149.813000 47.445175 9.417852 3.531708 1.718797 6.528212 14.033363 36.953200 149.813000

Antenna 32: 2459821

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
32 N02 RF_maintenance nn Temporal Discontinuties 65.395526 7.806622 54.116616 1.914256 3.584681 14.575296 8.193912 65.395526 20.277179

Antenna 32: 2459820

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
32 N02 RF_maintenance nn Temporal Discontinuties 50.351544 50.023709 11.825752 2.999050 2.331469 23.830093 42.318394 45.266283 50.351544

Antenna 32: 2459817

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
32 N02 RF_maintenance nn Temporal Discontinuties 51.048984 44.159946 14.713926 2.782155 0.586606 9.527108 18.106058 16.218602 51.048984

Antenna 32: 2459816

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
32 N02 RF_maintenance nn Temporal Discontinuties 51.830294 29.850488 32.557568 1.856119 2.322337 15.464851 13.446395 51.830294 38.597595

Antenna 32: 2459815

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
32 N02 RF_maintenance nn Temporal Discontinuties 42.781157 30.598530 36.414833 2.009225 2.588430 12.446353 10.960552 42.781157 33.521336

Antenna 32: 2459814

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
32 N02 RF_maintenance nn Shape nan nan nan nan nan nan nan nan nan

Antenna 32: 2459813

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
32 N02 RF_maintenance nn Shape nan nan nan inf inf nan nan nan nan
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